基于峰-谷分段积分算法的行走步态周期识别

摘要

将表面肌电信号(SEMS)作为信息源,提出一种基于峰—谷分段积分算法的人体行走步态周期识别方法.通过凌阳SPCE061A单片机对SEMS进行实时采集,使用RS232串行口与PC机进行通信,将SEMS的数字量信息传递给PC机.在Visual C++环境下建立步态周期识别界面,采集6位被测者行走时的8个下肢SEMS.实验结果表明,该方法能提高识别结果的准确性和可靠性.%This paper presents a walking gait cycle recognition based on Peak-valley Piecewise Integrator(PVPI) algorithm, it uses Surface Electromyogram Signal(SEMS) as information source. The SEMS signal can be real-time sampled by SPCE061A MCU, and communicate with PC through RS232. The digital value of signal can be delivered to the PC. The gait cycle identification experiment system is designed through Visual C++6.0 based on PVPI algorithm. The signals analysis are sampled from 8 SEMS of 6 bodies when walking. The results of the system show that the walking gait cycle identification method is accuracy and reliablity.